{"id":"W1926765961","doi":"10.1021/ja309294u","title":"Specific <sup>12</sup>C<sup>β</sup>D<sub>2</sub><sup>12</sup>C<sup>γ</sup>D<sub>2</sub>S<sup>13</sup>C<sup>ε</sup>HD<sub>2</sub> Isotopomer Labeling of Methionine To Characterize Protein Dynamics by <sup>1</sup>H and <sup>13</sup>C NMR Relaxation Dispersion","year":2012,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced NMR Techniques and Applications","field":"Chemistry","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Chemistry; Isotopomers; Protein dynamics; NMR spectra database; Relaxation (psychology); Deuterium; Population; Crystallography; Spectral line; Molecular dynamics; Computational chemistry; Molecule; Atomic physics; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001972381,0.0004683361,0.0001858472,0.000207457,0.0001934085,0.0002029937,0.0003708307,0.0005206974,0.005661551],"category_scores_gemma":[0.00026599,0.0002805718,0.0001642581,0.0002000039,0.0002940267,0.0003218389,0.0002923437,0.0006952556,0.002170635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001819354,"about_ca_system_score_gemma":0.000229389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000339549,"about_ca_topic_score_gemma":0.0009450683,"domain_scores_codex":[0.999891,0.00001221882,0.000006323893,0.00003711353,0.00003527837,0.00001796913],"domain_scores_gemma":[0.9998424,0.00003808664,0.00003520953,0.00003203908,0.00003357763,0.0000187288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002414305,0.000005229235,0.00008167396,0.00003219057,0.000001975881,0.00002954612,0.000007397323,0.00004709558,0.9981324,0.0000939618,0.0001918711,0.001352536],"study_design_scores_gemma":[0.000004691779,0.00005267611,0.0008611807,0.000003550442,0.000004494998,0.00009341985,0.00001496429,0.0006016435,0.9933432,0.0000449392,0.004969603,0.000005510591],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7775463,0.003093545,0.1888827,0.0008139011,0.0003858799,0.0003760968,0.002987973,0.002056053,0.02385761],"genre_scores_gemma":[0.8263603,0.003821708,0.1343889,0.0008023558,0.000182219,0.0005699612,0.004582513,0.0006478346,0.0286442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005661551,"threshold_uncertainty_score":0.01893973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089565366773717,"score_gpt":0.241597470284774,"score_spread":0.2307018166170369,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}